Shi Yayong, Qi Jianpeng, Wang Rui
School of Computer and Communication Engineering, University of Science and Technology Beijing (USTB), Beijing 100083, China.
Shunde Graduate School of University of Science and Technology Beijing, Foshan 528300, China.
Intell Syst Appl. 2022 May;14:200072. doi: 10.1016/j.iswa.2022.200072. Epub 2022 Mar 7.
In the period of Corona Virus Disease 2019 (COVID-19), millions of people participate in the discussion of COVID-19 on the Internet, which can easily trigger public opinion and threaten social stability. To find out the relationship between the intergroup variability in numbers and perspectives and the dynamic change of the number of infected people, this paper defines the public focus level to quantify the level of attention of people to the information related to an epidemic situation, and the POF model based on the level of epidemic focus is proposed. In this paper, we have carried out simulation experiments in small-world networks and scale-free networks, respectively, to explore the relationship between the model parameters and the spreading range and speed of each population. Furthermore, the paper also analyzed all the original microblog posts published by the People's Daily from January 14, 2020, to February 12, 2020, and compared the data simulated by the POF model with the real data from the People's Daily, the simulation data and the real data can be well fitted to prove the reliability of the model.
在2019年冠状病毒病(COVID-19)期间,数以百万计的人在互联网上参与关于COVID-19的讨论,这很容易引发公众舆论并威胁社会稳定。为了找出群体间数量和观点的变异性与感染者数量动态变化之间的关系,本文定义了公众关注水平来量化人们对疫情相关信息的关注程度,并提出了基于疫情关注水平的POF模型。本文分别在小世界网络和无标度网络中进行了模拟实验,以探索模型参数与各群体传播范围和速度之间的关系。此外,本文还分析了《人民日报》在2020年1月14日至2020年2月12日期间发布的所有原创微博文章,并将POF模型模拟的数据与《人民日报》的真实数据进行了比较,模拟数据与真实数据能够很好地拟合,证明了该模型的可靠性。